{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# python_[pandas](https://pandas.pydata.org/pandas-docs/stable/getting_started/10min.html)数据分析期末项目——国内[网络直播](https://www.liepin.com/city-gz/zhaopin/?dqs=050020&salary=&isAnalysis=true&init=1&searchType=1&fromSearchBtn=1&jobTitles=&industries=&industryType=&d_headId=8d08dfb4d6c8002f10a1c7c2dcc40355&d_ckId=8d08dfb4d6c8002f10a1c7c2dcc40355&d_sfrom=search_city&d_curPage=0&d_pageSize=40&siTag=&key=%E7%BD%91%E7%BB%9C%E7%9B%B4%E6%92%AD)职位的数据分析\n",
    "\n",
    "### [分析代码](https://gitee.com/JWFung/python_pandas_Learning_notes/blob/master/pandas_final%E8%BF%AD%E4%BB%A3%E4%BA%8C/python%E6%95%B0%E6%8D%AE%E5%88%86%E6%9E%90%E6%9C%9F%E6%9C%AB%E9%A1%B9%E7%9B%AE%E2%80%94%E2%80%94%E5%9B%BD%E5%86%85%E7%BD%91%E7%BB%9C%E7%9B%B4%E6%92%AD%E8%81%8C%E4%BD%8D%E7%9A%84%E6%95%B0%E6%8D%AE%E5%88%86%E6%9E%90.ipynb)\n",
    "\n",
    "|  项目人   | 冯静雯181013037 [Gitee仓库](https://gitee.com/JWFung/python_pandas_Learning_notes/tree/master/pandas_final%E8%BF%AD%E4%BB%A3%E4%BA%8C)  |\n",
    "|  ----  | ----  |\n",
    "| 数据交互可视化报告   | [index.html可视化报告-请下载](https://gitee.com/JWFung/python_pandas_Learning_notes/blob/master/pandas_final%E8%BF%AD%E4%BB%A3%E4%BA%8C/index.html) |\n",
    "| 数据来源   | [数据挖掘课](http://e.nfu.edu.cn/?redirect=0)同学提供的[中国猎聘网数据](https://www.liepin.com/city-gz/zhaopin/?init=1) |\n",
    "|  主要利用的数据   | 数据源总共有12个栏位，分析中主要用到学历要求、公司所在城市、职称、经验要求及工作职责这几个栏位  |\n",
    "|  分析目标  | 通过对中国猎聘网爬取的数据分析国内网络直播行业的招聘情况、能力要求提供给相关网络直播求职用  |\n",
    "|  价值宣言  | 网络直播职业求职者在搜索相关职职位时，只能看到相关的文字与某公司的职业要求等信息，对行职位的整体情况与要求不太了解，通过数据分析得出行业整体情况的可视化图表与分析文字，为网络直播求职者提供更多关于整个国内行业的信息。  |\n",
    " "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 读出表格"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>学历要求</th>\n",
       "      <th>经验</th>\n",
       "      <th>薪水</th>\n",
       "      <th>时间</th>\n",
       "      <th>职称</th>\n",
       "      <th>公司所在城市</th>\n",
       "      <th>公司地点</th>\n",
       "      <th>公司名称</th>\n",
       "      <th>链结</th>\n",
       "      <th>公司URL</th>\n",
       "      <th>行业分类</th>\n",
       "      <th>公司类型</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>本科及以上</td>\n",
       "      <td>3-5年</td>\n",
       "      <td>面议</td>\n",
       "      <td>2020年04月24日</td>\n",
       "      <td>60238-15665-公共协调项目管理经理(深圳)</td>\n",
       "      <td>深圳</td>\n",
       "      <td>深圳</td>\n",
       "      <td>腾讯</td>\n",
       "      <td>https://www.liepin.com/job/1927453413.shtml</td>\n",
       "      <td>https://www.liepin.com/company/7983148/</td>\n",
       "      <td>互联网/电商</td>\n",
       "      <td>中国500强</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>本科及以上</td>\n",
       "      <td>5-10年</td>\n",
       "      <td>20-40k·16薪</td>\n",
       "      <td>2020年04月24日</td>\n",
       "      <td>公共事务经理/高级经理（上海）</td>\n",
       "      <td>上海</td>\n",
       "      <td>上海</td>\n",
       "      <td>网易集团</td>\n",
       "      <td>https://www.liepin.com/job/1927546695.shtml</td>\n",
       "      <td>https://www.liepin.com/company/5964833/</td>\n",
       "      <td>互联网/电商</td>\n",
       "      <td>中国500强</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>学历不限</td>\n",
       "      <td>经验不限</td>\n",
       "      <td>面议</td>\n",
       "      <td>2020年04月22日</td>\n",
       "      <td>高级法律顾问/法律顾问（合同审核与法律风险控制方向 - 在线游戏事业部</td>\n",
       "      <td>广州</td>\n",
       "      <td>广州</td>\n",
       "      <td>网易集团</td>\n",
       "      <td>https://www.liepin.com/job/1927086751.shtml</td>\n",
       "      <td>https://www.liepin.com/company/5964833/</td>\n",
       "      <td>互联网/电商</td>\n",
       "      <td>中国500强</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>学历不限</td>\n",
       "      <td>经验不限</td>\n",
       "      <td>面议</td>\n",
       "      <td>2020年04月22日</td>\n",
       "      <td>高级法律顾问（合同审查与法律风险控制）</td>\n",
       "      <td>上海</td>\n",
       "      <td>上海</td>\n",
       "      <td>网易集团</td>\n",
       "      <td>https://www.liepin.com/job/1927086739.shtml</td>\n",
       "      <td>https://www.liepin.com/company/5964833/</td>\n",
       "      <td>互联网/电商</td>\n",
       "      <td>中国500强</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>学历不限</td>\n",
       "      <td>3-5年</td>\n",
       "      <td>面议</td>\n",
       "      <td>2020年04月09日</td>\n",
       "      <td>新零售技术事业群-算法专家-淘宝直播-淘系技术部</td>\n",
       "      <td>杭州</td>\n",
       "      <td>杭州</td>\n",
       "      <td>阿里巴巴</td>\n",
       "      <td>https://www.liepin.com/job/1927315503.shtml</td>\n",
       "      <td>https://www.liepin.com/company/1072424/</td>\n",
       "      <td>互联网/电商</td>\n",
       "      <td>中国500强</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>507</th>\n",
       "      <td>大专及以上</td>\n",
       "      <td>经验不限</td>\n",
       "      <td>面议</td>\n",
       "      <td>2020年03月21日</td>\n",
       "      <td>微特喜网络-直播执行岗</td>\n",
       "      <td>南京</td>\n",
       "      <td>南京-宁南</td>\n",
       "      <td>中国(南京)软件谷管理委员会</td>\n",
       "      <td>https://www.liepin.com/job/1926697249.shtml</td>\n",
       "      <td>https://www.liepin.com/company/8602256/</td>\n",
       "      <td>政务/公共服务</td>\n",
       "      <td>其他</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>508</th>\n",
       "      <td>本科及以上</td>\n",
       "      <td>经验不限</td>\n",
       "      <td>5-6k·12薪</td>\n",
       "      <td>2019年02月27日</td>\n",
       "      <td>影音技术工程师</td>\n",
       "      <td>北京</td>\n",
       "      <td>北京</td>\n",
       "      <td>共青团中央网络</td>\n",
       "      <td>https://www.liepin.com/job/1917355465.shtml</td>\n",
       "      <td>https://www.liepin.com/company/7861283/</td>\n",
       "      <td>政务/公共服务</td>\n",
       "      <td>其他</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>509</th>\n",
       "      <td>大专及以上</td>\n",
       "      <td>经验不限</td>\n",
       "      <td>4-7k·12薪</td>\n",
       "      <td>2020年04月13日</td>\n",
       "      <td>短视频制作</td>\n",
       "      <td>成都</td>\n",
       "      <td>成都-双流区</td>\n",
       "      <td>成都蓉橙九天生物科技有限公司</td>\n",
       "      <td>https://www.liepin.com/job/1925244277.shtml</td>\n",
       "      <td>https://www.liepin.com/company/9331826/</td>\n",
       "      <td>农林牧渔</td>\n",
       "      <td>其他</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>510</th>\n",
       "      <td>本科及以上</td>\n",
       "      <td>10年以上</td>\n",
       "      <td>90-118k·12薪</td>\n",
       "      <td>2020年02月12日</td>\n",
       "      <td>副总经理</td>\n",
       "      <td>江西</td>\n",
       "      <td>江西</td>\n",
       "      <td>某集团公司</td>\n",
       "      <td>https://www.liepin.com/a/18714993.shtml</td>\n",
       "      <td>NaN</td>\n",
       "      <td>农林牧渔</td>\n",
       "      <td>其他</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>511</th>\n",
       "      <td>本科及以上</td>\n",
       "      <td>经验不限</td>\n",
       "      <td>4-8k·12薪</td>\n",
       "      <td>2019年08月27日</td>\n",
       "      <td>运营经理/主管</td>\n",
       "      <td>杭州</td>\n",
       "      <td>杭州</td>\n",
       "      <td>杭州来聚网络科技有限公司</td>\n",
       "      <td>https://www.liepin.com/job/1922691015.shtml</td>\n",
       "      <td>https://www.liepin.com/company/9249841/</td>\n",
       "      <td>其他行业</td>\n",
       "      <td>其他</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>512 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      学历要求     经验           薪水           时间  \\\n",
       "0    本科及以上   3-5年           面议  2020年04月24日   \n",
       "1    本科及以上  5-10年   20-40k·16薪  2020年04月24日   \n",
       "2     学历不限   经验不限           面议  2020年04月22日   \n",
       "3     学历不限   经验不限           面议  2020年04月22日   \n",
       "4     学历不限   3-5年           面议  2020年04月09日   \n",
       "..     ...    ...          ...          ...   \n",
       "507  大专及以上   经验不限           面议  2020年03月21日   \n",
       "508  本科及以上   经验不限     5-6k·12薪  2019年02月27日   \n",
       "509  大专及以上   经验不限     4-7k·12薪  2020年04月13日   \n",
       "510  本科及以上  10年以上  90-118k·12薪  2020年02月12日   \n",
       "511  本科及以上   经验不限     4-8k·12薪  2019年08月27日   \n",
       "\n",
       "                                      职称 公司所在城市    公司地点            公司名称  \\\n",
       "0             60238-15665-公共协调项目管理经理(深圳)     深圳      深圳              腾讯   \n",
       "1                        公共事务经理/高级经理（上海）     上海      上海            网易集团   \n",
       "2    高级法律顾问/法律顾问（合同审核与法律风险控制方向 - 在线游戏事业部     广州      广州            网易集团   \n",
       "3                    高级法律顾问（合同审查与法律风险控制）     上海      上海            网易集团   \n",
       "4               新零售技术事业群-算法专家-淘宝直播-淘系技术部     杭州      杭州            阿里巴巴   \n",
       "..                                   ...    ...     ...             ...   \n",
       "507                          微特喜网络-直播执行岗     南京   南京-宁南  中国(南京)软件谷管理委员会   \n",
       "508                              影音技术工程师     北京      北京         共青团中央网络   \n",
       "509                                短视频制作     成都  成都-双流区  成都蓉橙九天生物科技有限公司   \n",
       "510                                 副总经理     江西      江西           某集团公司   \n",
       "511                              运营经理/主管     杭州      杭州    杭州来聚网络科技有限公司   \n",
       "\n",
       "                                              链结  \\\n",
       "0    https://www.liepin.com/job/1927453413.shtml   \n",
       "1    https://www.liepin.com/job/1927546695.shtml   \n",
       "2    https://www.liepin.com/job/1927086751.shtml   \n",
       "3    https://www.liepin.com/job/1927086739.shtml   \n",
       "4    https://www.liepin.com/job/1927315503.shtml   \n",
       "..                                           ...   \n",
       "507  https://www.liepin.com/job/1926697249.shtml   \n",
       "508  https://www.liepin.com/job/1917355465.shtml   \n",
       "509  https://www.liepin.com/job/1925244277.shtml   \n",
       "510      https://www.liepin.com/a/18714993.shtml   \n",
       "511  https://www.liepin.com/job/1922691015.shtml   \n",
       "\n",
       "                                       公司URL     行业分类    公司类型  \n",
       "0    https://www.liepin.com/company/7983148/   互联网/电商  中国500强  \n",
       "1    https://www.liepin.com/company/5964833/   互联网/电商  中国500强  \n",
       "2    https://www.liepin.com/company/5964833/   互联网/电商  中国500强  \n",
       "3    https://www.liepin.com/company/5964833/   互联网/电商  中国500强  \n",
       "4    https://www.liepin.com/company/1072424/   互联网/电商  中国500强  \n",
       "..                                       ...      ...     ...  \n",
       "507  https://www.liepin.com/company/8602256/  政务/公共服务      其他  \n",
       "508  https://www.liepin.com/company/7861283/  政务/公共服务      其他  \n",
       "509  https://www.liepin.com/company/9331826/     农林牧渔      其他  \n",
       "510                                      NaN     农林牧渔      其他  \n",
       "511  https://www.liepin.com/company/9249841/     其他行业      其他  \n",
       "\n",
       "[512 rows x 12 columns]"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "df=pd.read_excel(\"网络直播.xlsx\").drop(\"Unnamed: 0\",axis=1)#导入数据\n",
    "df\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 清洗数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 部分公司地点为“无”，通过excal查看照片链接手动填入信息并删去结束招聘的公司信息。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A.筛选出无城市数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](images/shaixuan.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "B.手动添加数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](images/tianjia.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 进行数据的分进合击，为做图做准备"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "[split](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.str.split.html)、[join](https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.join.html)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "直播职位城市招聘数量=df.groupby(\"公司所在城市\").agg({\"职称\":\"count\"})#数据分租"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 重新设置索引，生成数据列表，再做成区域地图。\n",
    "直播职位城市招聘数量=直播职位城市招聘数量.reset_index()\n",
    "直播职位城市数量列表=直播职位城市招聘数量[\"公司所在城市\"].to_list()\n",
    "直播职位数量列表=直播职位城市招聘数量[\"职称\"].to_list()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 交互式数据可视化 "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<strong> 制图模块介绍：[pyecharts制作图](https://pyecharts.org/#/)</strong>\n",
    "* [地图链接](http://gallery.pyecharts.org/#/Map/map_china_cities)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  国内各城市网络直播职位数量分布地图\n",
    "* 思考: 在收集到的数据中有相关职位的公司位置信息，通过地图可视化，展示全国各城市招聘网络直播职位的数量，从而直观地展示求职者目标就业城市的网络直播职位的招聘数量，同时展示哪一个城市比较缺乏网络直播职位人才。求职者可以根据分布地图分析相关城市的职位竞争激烈程度，从而确定就业城市。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从下面图表可知，网络直播职位需求多分布在东部沿海地区与长江流域城市，可以看出经济发展较好的地方网络直播的人才需求更大，求职者可以考虑去往东部沿海地区就业，东部沿海地区的机会更多，其中，北京、上海、广州和深圳的需求较高。\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
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       "                {\n",
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       "            \"roam\": true,\n",
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       "            \"emphasis\": {}\n",
       "        }\n",
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       "    \"legend\": [\n",
       "        {\n",
       "            \"data\": [\n",
       "                \" \"\n",
       "            ],\n",
       "            \"selected\": {\n",
       "                \" \": true\n",
       "            },\n",
       "            \"show\": true,\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10,\n",
       "            \"itemWidth\": 25,\n",
       "            \"itemHeight\": 14\n",
       "        }\n",
       "    ],\n",
       "    \"tooltip\": {\n",
       "        \"show\": true,\n",
       "        \"trigger\": \"item\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
       "            \"type\": \"line\"\n",
       "        },\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 14\n",
       "        },\n",
       "        \"borderWidth\": 0\n",
       "    },\n",
       "    \"title\": [\n",
       "        {\n",
       "            \"text\": \"\\u7f51\\u7edc\\u76f4\\u64ad\\u804c\\u4f4d\\u5730\\u56fe\\uff08\\u56fd\\u5185\\uff09\",\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10\n",
       "        }\n",
       "    ],\n",
       "    \"visualMap\": {\n",
       "        \"show\": true,\n",
       "        \"type\": \"continuous\",\n",
       "        \"min\": 0,\n",
       "        \"max\": 100,\n",
       "        \"inRange\": {\n",
       "            \"color\": [\n",
       "                \"#50a3ba\",\n",
       "                \"#eac763\",\n",
       "                \"#d94e5d\"\n",
       "            ]\n",
       "        },\n",
       "        \"calculable\": true,\n",
       "        \"inverse\": false,\n",
       "        \"splitNumber\": 5,\n",
       "        \"orient\": \"vertical\",\n",
       "        \"showLabel\": true,\n",
       "        \"itemWidth\": 20,\n",
       "        \"itemHeight\": 140,\n",
       "        \"borderWidth\": 0\n",
       "    }\n",
       "};\n",
       "                chart_94abceac3f8443ba8fb64c5f8670229b.setOption(option_94abceac3f8443ba8fb64c5f8670229b);\n",
       "        });\n",
       "    </script>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x25386125a58>"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "from pyecharts import options as opts\n",
    "from pyecharts.charts import Map,Bar,Line\n",
    "from pyecharts.faker import Faker\n",
    "\n",
    "c = (\n",
    "    Map()\n",
    "    .add(\n",
    "        \" \",\n",
    "        [list(z) for z in zip(直播职位城市数量列表, 直播职位数量列表)],\n",
    "        \"china-cities\",\n",
    "        label_opts=opts.LabelOpts(is_show=False),\n",
    "    )\n",
    "    .set_global_opts(\n",
    "        title_opts=opts.TitleOpts(title=\"网络直播职位地图（国内）\"),\n",
    "        visualmap_opts=opts.VisualMapOpts(),\n",
    "        \n",
    "    )\n",
    "   # .render(\"教育直播地图.html\")\n",
    ")\n",
    "c.render_notebook()#在notebook渲染图表"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 国内网络直播职位的学历要求\n",
    "* [饼状图制图链接](http://gallery.pyecharts.org/#/Pie/pie_radius)\n",
    "* 思考：数据中有职位的学历要求，求职者在找职位时会考虑自己的学历是否符合招聘要求，通过本分析国内网络直播职位的学历分析图表，求职者可以直观地得知网络直播职位对学历的整体要求与自己学历所匹配的职位的比例，可以给求职者提供信息。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A.分进合击数据，为作图做准备"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [],
   "source": [
    "学历要求数量=df.groupby(\"学历要求\").agg({\"职称\":\"count\"})#分组"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[8, 1, 150, 95, 189, 6, 63]"
      ]
     },
     "execution_count": 103,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "学历要求数量=学历要求数量.reset_index()# 重新设置索引，生成数据列表，再做图。\n",
    "学历要求list=学历要求数量[\"学历要求\"].to_list()\n",
    "学历要求数量list=学历要求数量[\"职称\"].to_list()\n",
    "学历要求数量list"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "B.作图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
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       "\n",
       "<script>\n",
       "        require(['echarts'], function(echarts) {\n",
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       "                \"formatter\": \"{a} <br/>{b}: {c} ({d}%)\",\n",
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       "                \"\\u4e2d\\u4e13/\\u4e2d\\u6280\\u53ca\\u4ee5\\u4e0a\",\n",
       "                \"\\u535a\\u58eb\\u540e\",\n",
       "                \"\\u5927\\u4e13\\u53ca\\u4ee5\\u4e0a\",\n",
       "                \"\\u5b66\\u5386\\u4e0d\\u9650\",\n",
       "                \"\\u672c\\u79d1\\u53ca\\u4ee5\\u4e0a\",\n",
       "                \"\\u7855\\u58eb\\u53ca\\u4ee5\\u4e0a\",\n",
       "                \"\\u7edf\\u62db\\u672c\\u79d1\"\n",
       "            ],\n",
       "            \"selected\": {},\n",
       "            \"show\": true,\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10,\n",
       "            \"itemWidth\": 25,\n",
       "            \"itemHeight\": 14\n",
       "        }\n",
       "    ],\n",
       "    \"tooltip\": {\n",
       "        \"show\": true,\n",
       "        \"trigger\": \"item\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
       "            \"type\": \"line\"\n",
       "        },\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 14\n",
       "        },\n",
       "        \"borderWidth\": 0\n",
       "    },\n",
       "    \"title\": [\n",
       "        {\n",
       "            \"text\": \"\\u7f51\\u7edc\\u76f4\\u64ad\\u5c97\\u4f4d\\u5b66\\u5386\\u8981\\u6c42\",\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10\n",
       "        }\n",
       "    ]\n",
       "};\n",
       "                chart_da2633b462c94484a7982c8ae9db8d10.setOption(option_da2633b462c94484a7982c8ae9db8d10);\n",
       "        });\n",
       "    </script>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x25381d5ce10>"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "import pyecharts.options as opts\n",
    "from pyecharts.charts import Pie\n",
    "\n",
    "\"\"\"\n",
    "Gallery 使用 pyecharts 1.1.0\n",
    "参考地址: https://echarts.baidu.com/examples/editor.html?c=pie-doughnut\n",
    "\n",
    "目前无法实现的功能:\n",
    "\n",
    "1、饼状图中间的图例名称暂时无法显示\n",
    "\"\"\"\n",
    "\n",
    "x_data = 学历要求list\n",
    "y_data = 学历要求数量list\n",
    "\n",
    "(\n",
    "    Pie()#init_opts=opts.InitOpts(width=\"1600px\", height=\"1000px\"))\n",
    "    .add(\n",
    "        series_name=\"\",\n",
    "        data_pair=[list(z) for z in zip(x_data, y_data)],\n",
    "        radius=[\"50%\", \"70%\"],\n",
    "        label_opts=opts.LabelOpts(is_show=False, position=\"center\"),\n",
    "    )\n",
    "    .set_global_opts(title_opts=opts.TitleOpts(title=\"网络直播岗位学历要求\"),\n",
    "                    )\n",
    "    .set_series_opts(\n",
    "        tooltip_opts=opts.TooltipOpts(\n",
    "            trigger=\"item\", formatter=\"{a} <br/>{b}: {c} ({d}%)\"\n",
    "        ),\n",
    "        # label_opts=opts.LabelOpts(formatter=\"{b}: {c}\")\n",
    "    )\n",
    "   # .render(\"网络直播职位学历要求.html\")#生成html#\n",
    " ).render_notebook()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 网络直播对学历要求柱形图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<script>\n",
       "    require.config({\n",
       "        paths: {\n",
       "            'echarts':'https://assets.pyecharts.org/assets/echarts.min'\n",
       "        }\n",
       "    });\n",
       "</script>\n",
       "\n",
       "        <div id=\"77f94fca2f1244e688b203b4ead01e41\" style=\"width:900px; height:500px;\"></div>\n",
       "\n",
       "<script>\n",
       "        require(['echarts'], function(echarts) {\n",
       "                var chart_77f94fca2f1244e688b203b4ead01e41 = echarts.init(\n",
       "                    document.getElementById('77f94fca2f1244e688b203b4ead01e41'), 'white', {renderer: 'canvas'});\n",
       "                var option_77f94fca2f1244e688b203b4ead01e41 = {\n",
       "    \"animation\": true,\n",
       "    \"animationThreshold\": 2000,\n",
       "    \"animationDuration\": 1000,\n",
       "    \"animationEasing\": \"cubicOut\",\n",
       "    \"animationDelay\": 0,\n",
       "    \"animationDurationUpdate\": 300,\n",
       "    \"animationEasingUpdate\": \"cubicOut\",\n",
       "    \"animationDelayUpdate\": 0,\n",
       "    \"color\": [\n",
       "        \"#c23531\",\n",
       "        \"#2f4554\",\n",
       "        \"#61a0a8\",\n",
       "        \"#d48265\",\n",
       "        \"#749f83\",\n",
       "        \"#ca8622\",\n",
       "        \"#bda29a\",\n",
       "        \"#6e7074\",\n",
       "        \"#546570\",\n",
       "        \"#c4ccd3\",\n",
       "        \"#f05b72\",\n",
       "        \"#ef5b9c\",\n",
       "        \"#f47920\",\n",
       "        \"#905a3d\",\n",
       "        \"#fab27b\",\n",
       "        \"#2a5caa\",\n",
       "        \"#444693\",\n",
       "        \"#726930\",\n",
       "        \"#b2d235\",\n",
       "        \"#6d8346\",\n",
       "        \"#ac6767\",\n",
       "        \"#1d953f\",\n",
       "        \"#6950a1\",\n",
       "        \"#918597\"\n",
       "    ],\n",
       "    \"series\": [\n",
       "        {\n",
       "            \"type\": \"bar\",\n",
       "            \"name\": \"\\u5b66\\u5386\\u8981\\u6c42\\u6570\\u91cf\",\n",
       "            \"data\": [\n",
       "                8,\n",
       "                1,\n",
       "                150,\n",
       "                95,\n",
       "                189,\n",
       "                6,\n",
       "                63\n",
       "            ],\n",
       "            \"barCategoryGap\": \"20%\",\n",
       "            \"label\": {\n",
       "                \"show\": true,\n",
       "                \"position\": \"top\",\n",
       "                \"margin\": 8\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"legend\": [\n",
       "        {\n",
       "            \"data\": [\n",
       "                \"\\u5b66\\u5386\\u8981\\u6c42\\u6570\\u91cf\"\n",
       "            ],\n",
       "            \"selected\": {\n",
       "                \"\\u5b66\\u5386\\u8981\\u6c42\\u6570\\u91cf\": true\n",
       "            },\n",
       "            \"show\": true,\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10,\n",
       "            \"itemWidth\": 25,\n",
       "            \"itemHeight\": 14\n",
       "        }\n",
       "    ],\n",
       "    \"tooltip\": {\n",
       "        \"show\": true,\n",
       "        \"trigger\": \"item\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
       "            \"type\": \"line\"\n",
       "        },\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 14\n",
       "        },\n",
       "        \"borderWidth\": 0\n",
       "    },\n",
       "    \"xAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            },\n",
       "            \"data\": [\n",
       "                \"\\u4e2d\\u4e13/\\u4e2d\\u6280\\u53ca\\u4ee5\\u4e0a\",\n",
       "                \"\\u535a\\u58eb\\u540e\",\n",
       "                \"\\u5927\\u4e13\\u53ca\\u4ee5\\u4e0a\",\n",
       "                \"\\u5b66\\u5386\\u4e0d\\u9650\",\n",
       "                \"\\u672c\\u79d1\\u53ca\\u4ee5\\u4e0a\",\n",
       "                \"\\u7855\\u58eb\\u53ca\\u4ee5\\u4e0a\",\n",
       "                \"\\u7edf\\u62db\\u672c\\u79d1\"\n",
       "            ]\n",
       "        }\n",
       "    ],\n",
       "    \"yAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"title\": [\n",
       "        {\n",
       "            \"text\": \"\\u7f51\\u7edc\\u76f4\\u64ad\\u5b66\\u5386\\u8981\\u6c42\\u60c5\\u51b5\",\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10\n",
       "        }\n",
       "    ]\n",
       "};\n",
       "                chart_77f94fca2f1244e688b203b4ead01e41.setOption(option_77f94fca2f1244e688b203b4ead01e41);\n",
       "        });\n",
       "    </script>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x25381d2e9b0>"
      ]
     },
     "execution_count": 105,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def xueli() -> Bar:\n",
    "  \n",
    "    bar = (\n",
    "        Bar()\n",
    "        .add_xaxis(list(学历要求数量.学历要求))\n",
    "        .add_yaxis(\"学历要求数量\",list(学历要求数量.职称))\n",
    "        .set_global_opts(title_opts=opts.TitleOpts(title=\"网络直播学历要求情况\"))\n",
    "    )\n",
    "\n",
    "\n",
    "    return bar\n",
    "\n",
    "xueli().render_notebook()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 国内网络直播职位的经验要求\n",
    "* [玫瑰图](http://gallery.pyecharts.org/#/Pie/customized_pie)\n",
    "* 从下图可知，"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A.数据准备"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[133, 7, 157, 75, 3, 137]"
      ]
     },
     "execution_count": 106,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "工作经验要求=df.groupby(\"经验\").agg({\"职称\":\"count\"})\n",
    "工作经验要求=工作经验要求.reset_index()\n",
    "工作经验要求list=工作经验要求[\"经验\"].to_list()\n",
    "工作经验要求数量list=工作经验要求[\"职称\"].to_list()\n",
    "工作经验要求数量list"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "B.作图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<script>\n",
       "    require.config({\n",
       "        paths: {\n",
       "            'echarts':'https://assets.pyecharts.org/assets/echarts.min'\n",
       "        }\n",
       "    });\n",
       "</script>\n",
       "\n",
       "        <div id=\"1d6dd7161c344100b8cefecd37237eb9\" style=\"width:900px; height:500px;\"></div>\n",
       "\n",
       "<script>\n",
       "        require(['echarts'], function(echarts) {\n",
       "                var chart_1d6dd7161c344100b8cefecd37237eb9 = echarts.init(\n",
       "                    document.getElementById('1d6dd7161c344100b8cefecd37237eb9'), 'white', {renderer: 'canvas'});\n",
       "                var option_1d6dd7161c344100b8cefecd37237eb9 = {\n",
       "    \"animation\": true,\n",
       "    \"animationThreshold\": 2000,\n",
       "    \"animationDuration\": 1000,\n",
       "    \"animationEasing\": \"cubicOut\",\n",
       "    \"animationDelay\": 0,\n",
       "    \"animationDurationUpdate\": 300,\n",
       "    \"animationEasingUpdate\": \"cubicOut\",\n",
       "    \"animationDelayUpdate\": 0,\n",
       "    \"color\": [\n",
       "        \"#c23531\",\n",
       "        \"#2f4554\",\n",
       "        \"#61a0a8\",\n",
       "        \"#d48265\",\n",
       "        \"#749f83\",\n",
       "        \"#ca8622\",\n",
       "        \"#bda29a\",\n",
       "        \"#6e7074\",\n",
       "        \"#546570\",\n",
       "        \"#c4ccd3\",\n",
       "        \"#f05b72\",\n",
       "        \"#ef5b9c\",\n",
       "        \"#f47920\",\n",
       "        \"#905a3d\",\n",
       "        \"#fab27b\",\n",
       "        \"#2a5caa\",\n",
       "        \"#444693\",\n",
       "        \"#726930\",\n",
       "        \"#b2d235\",\n",
       "        \"#6d8346\",\n",
       "        \"#ac6767\",\n",
       "        \"#1d953f\",\n",
       "        \"#6950a1\",\n",
       "        \"#918597\"\n",
       "    ],\n",
       "    \"series\": [\n",
       "        {\n",
       "            \"type\": \"pie\",\n",
       "            \"clockwise\": true,\n",
       "            \"data\": [\n",
       "                {\n",
       "                    \"name\": \"1-3\\u5e74\",\n",
       "                    \"value\": 133\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"10\\u5e74\\u4ee5\\u4e0a\",\n",
       "                    \"value\": 7\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"3-5\\u5e74\",\n",
       "                    \"value\": 157\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"5-10\\u5e74\",\n",
       "                    \"value\": 75\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u4e00\\u5e74\\u4ee5\\u4e0b\",\n",
       "                    \"value\": 3\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u7ecf\\u9a8c\\u4e0d\\u9650\",\n",
       "                    \"value\": 137\n",
       "                }\n",
       "            ],\n",
       "            \"radius\": [\n",
       "                \"30%\",\n",
       "                \"75%\"\n",
       "            ],\n",
       "            \"center\": [\n",
       "                \"25%\",\n",
       "                \"50%\"\n",
       "            ],\n",
       "            \"roseType\": \"radius\",\n",
       "            \"label\": {\n",
       "                \"show\": false,\n",
       "                \"position\": \"top\",\n",
       "                \"margin\": 8\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"legend\": [\n",
       "        {\n",
       "            \"data\": [\n",
       "                \"1-3\\u5e74\",\n",
       "                \"10\\u5e74\\u4ee5\\u4e0a\",\n",
       "                \"3-5\\u5e74\",\n",
       "                \"5-10\\u5e74\",\n",
       "                \"\\u4e00\\u5e74\\u4ee5\\u4e0b\",\n",
       "                \"\\u7ecf\\u9a8c\\u4e0d\\u9650\"\n",
       "            ],\n",
       "            \"selected\": {},\n",
       "            \"show\": true,\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10,\n",
       "            \"itemWidth\": 25,\n",
       "            \"itemHeight\": 14\n",
       "        }\n",
       "    ],\n",
       "    \"tooltip\": {\n",
       "        \"show\": true,\n",
       "        \"trigger\": \"item\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
       "            \"type\": \"line\"\n",
       "        },\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 14\n",
       "        },\n",
       "        \"borderWidth\": 0\n",
       "    },\n",
       "    \"title\": [\n",
       "        {\n",
       "            \"text\": \"\\u7f51\\u7edc\\u76f4\\u64ad\\u5c97\\u4f4d\\u7ecf\\u9a8c\\u8981\\u6c42\",\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10\n",
       "        }\n",
       "    ]\n",
       "};\n",
       "                chart_1d6dd7161c344100b8cefecd37237eb9.setOption(option_1d6dd7161c344100b8cefecd37237eb9);\n",
       "        });\n",
       "    </script>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x25386125cc0>"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "v =工作经验要求list# Faker.choose()\n",
    "i=工作经验要求数量list\n",
    "c = (\n",
    "    Pie()\n",
    "    .add(\n",
    "        \"\",\n",
    "        [list(z) for z in zip(v, i)],\n",
    "        radius=[\"30%\", \"75%\"],\n",
    "        center=[\"25%\", \"50%\"],\n",
    "        rosetype=\"radius\",\n",
    "        label_opts=opts.LabelOpts(is_show=False),\n",
    "    )\n",
    "    .set_global_opts(title_opts=opts.TitleOpts(title=\"网络直播岗位经验要求\"))\n",
    "   \n",
    "   # .render(\"网络直播职位经验要求.html\")\n",
    ")\n",
    "c.render_notebook()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 网络直播对经验要求折线图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<script>\n",
       "    require.config({\n",
       "        paths: {\n",
       "            'echarts':'https://assets.pyecharts.org/assets/echarts.min'\n",
       "        }\n",
       "    });\n",
       "</script>\n",
       "\n",
       "        <div id=\"163bcc9e3f5044bca9638685ed819402\" style=\"width:900px; height:500px;\"></div>\n",
       "\n",
       "<script>\n",
       "        require(['echarts'], function(echarts) {\n",
       "                var chart_163bcc9e3f5044bca9638685ed819402 = echarts.init(\n",
       "                    document.getElementById('163bcc9e3f5044bca9638685ed819402'), 'white', {renderer: 'canvas'});\n",
       "                var option_163bcc9e3f5044bca9638685ed819402 = {\n",
       "    \"animation\": true,\n",
       "    \"animationThreshold\": 2000,\n",
       "    \"animationDuration\": 1000,\n",
       "    \"animationEasing\": \"cubicOut\",\n",
       "    \"animationDelay\": 0,\n",
       "    \"animationDurationUpdate\": 300,\n",
       "    \"animationEasingUpdate\": \"cubicOut\",\n",
       "    \"animationDelayUpdate\": 0,\n",
       "    \"color\": [\n",
       "        \"#c23531\",\n",
       "        \"#2f4554\",\n",
       "        \"#61a0a8\",\n",
       "        \"#d48265\",\n",
       "        \"#749f83\",\n",
       "        \"#ca8622\",\n",
       "        \"#bda29a\",\n",
       "        \"#6e7074\",\n",
       "        \"#546570\",\n",
       "        \"#c4ccd3\",\n",
       "        \"#f05b72\",\n",
       "        \"#ef5b9c\",\n",
       "        \"#f47920\",\n",
       "        \"#905a3d\",\n",
       "        \"#fab27b\",\n",
       "        \"#2a5caa\",\n",
       "        \"#444693\",\n",
       "        \"#726930\",\n",
       "        \"#b2d235\",\n",
       "        \"#6d8346\",\n",
       "        \"#ac6767\",\n",
       "        \"#1d953f\",\n",
       "        \"#6950a1\",\n",
       "        \"#918597\"\n",
       "    ],\n",
       "    \"series\": [\n",
       "        {\n",
       "            \"type\": \"line\",\n",
       "            \"name\": \"\\u7ecf\\u9a8c\\u8981\\u6c42\\u6570\\u91cf\",\n",
       "            \"connectNulls\": false,\n",
       "            \"symbolSize\": 4,\n",
       "            \"showSymbol\": true,\n",
       "            \"smooth\": false,\n",
       "            \"step\": false,\n",
       "            \"data\": [\n",
       "                [\n",
       "                    \"1-3\\u5e74\",\n",
       "                    133\n",
       "                ],\n",
       "                [\n",
       "                    \"10\\u5e74\\u4ee5\\u4e0a\",\n",
       "                    7\n",
       "                ],\n",
       "                [\n",
       "                    \"3-5\\u5e74\",\n",
       "                    157\n",
       "                ],\n",
       "                [\n",
       "                    \"5-10\\u5e74\",\n",
       "                    75\n",
       "                ],\n",
       "                [\n",
       "                    \"\\u4e00\\u5e74\\u4ee5\\u4e0b\",\n",
       "                    3\n",
       "                ],\n",
       "                [\n",
       "                    \"\\u7ecf\\u9a8c\\u4e0d\\u9650\",\n",
       "                    137\n",
       "                ]\n",
       "            ],\n",
       "            \"hoverAnimation\": true,\n",
       "            \"label\": {\n",
       "                \"show\": true,\n",
       "                \"position\": \"top\",\n",
       "                \"margin\": 8\n",
       "            },\n",
       "            \"lineStyle\": {\n",
       "                \"show\": true,\n",
       "                \"width\": 1,\n",
       "                \"opacity\": 1,\n",
       "                \"curveness\": 0,\n",
       "                \"type\": \"solid\"\n",
       "            },\n",
       "            \"areaStyle\": {\n",
       "                \"opacity\": 0\n",
       "            },\n",
       "            \"zlevel\": 0,\n",
       "            \"z\": 0\n",
       "        }\n",
       "    ],\n",
       "    \"legend\": [\n",
       "        {\n",
       "            \"data\": [\n",
       "                \"\\u7ecf\\u9a8c\\u8981\\u6c42\\u6570\\u91cf\"\n",
       "            ],\n",
       "            \"selected\": {\n",
       "                \"\\u7ecf\\u9a8c\\u8981\\u6c42\\u6570\\u91cf\": true\n",
       "            },\n",
       "            \"show\": true,\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10,\n",
       "            \"itemWidth\": 25,\n",
       "            \"itemHeight\": 14\n",
       "        }\n",
       "    ],\n",
       "    \"tooltip\": {\n",
       "        \"show\": true,\n",
       "        \"trigger\": \"item\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
       "            \"type\": \"line\"\n",
       "        },\n",
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       "            \"fontSize\": 14\n",
       "        },\n",
       "        \"borderWidth\": 0\n",
       "    },\n",
       "    \"xAxis\": [\n",
       "        {\n",
       "            \"show\": true,\n",
       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            },\n",
       "            \"data\": [\n",
       "                \"1-3\\u5e74\",\n",
       "                \"10\\u5e74\\u4ee5\\u4e0a\",\n",
       "                \"3-5\\u5e74\",\n",
       "                \"5-10\\u5e74\",\n",
       "                \"\\u4e00\\u5e74\\u4ee5\\u4e0b\",\n",
       "                \"\\u7ecf\\u9a8c\\u4e0d\\u9650\"\n",
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       "    \"yAxis\": [\n",
       "        {\n",
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       "            \"scale\": false,\n",
       "            \"nameLocation\": \"end\",\n",
       "            \"nameGap\": 15,\n",
       "            \"gridIndex\": 0,\n",
       "            \"inverse\": false,\n",
       "            \"offset\": 0,\n",
       "            \"splitNumber\": 5,\n",
       "            \"minInterval\": 0,\n",
       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
       "                \"lineStyle\": {\n",
       "                    \"show\": true,\n",
       "                    \"width\": 1,\n",
       "                    \"opacity\": 1,\n",
       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"title\": [\n",
       "        {\n",
       "            \"text\": \"\\u7f51\\u7edc\\u76f4\\u64ad\\u62db\\u8058\\u5bf9\\u7ecf\\u9a8c\\u8981\\u6c42\",\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10\n",
       "        }\n",
       "    ]\n",
       "};\n",
       "                chart_163bcc9e3f5044bca9638685ed819402.setOption(option_163bcc9e3f5044bca9638685ed819402);\n",
       "        });\n",
       "    </script>\n"
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     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def jingyan() -> Bar:\n",
    "  \n",
    "    line = (\n",
    "        Line()\n",
    "        .add_xaxis(list(工作经验要求.经验))\n",
    "        .add_yaxis(\"经验要求数量\", list(工作经验要求.职称))\n",
    "        .set_global_opts(title_opts=opts.TitleOpts(title=\"网络直播招聘对经验要求\"))\n",
    "    )\n",
    "\n",
    "    \n",
    "  \n",
    "\n",
    "    return line\n",
    "\n",
    "jingyan().render_notebook()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 网络直播各薪水段情况"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\12643\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  \n"
     ]
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       "                \"5-12k\",\n",
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       "                \"10-22k\",\n",
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       "            \"splitLine\": {\n",
       "                \"show\": false,\n",
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       "                    \"width\": 1,\n",
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       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
       "                }\n",
       "            }\n",
       "        }\n",
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       "    \"title\": [\n",
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       "            \"padding\": 5,\n",
       "            \"itemGap\": 10\n",
       "        }\n",
       "    ]\n",
       "};\n",
       "                chart_a0a5fddce2104b5eb4f8938eb7e42728.setOption(option_a0a5fddce2104b5eb4f8938eb7e42728);\n",
       "        });\n",
       "    </script>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x25386125400>"
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     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "薪水拆分=df[df[\"薪水\"].str.contains(\"·\")]\n",
    "\n",
    "薪水拆分列表=list()\n",
    "for x in 薪水拆分[\"薪水\"].to_list():\n",
    "    薪水拆分列表.append(x.split(\"·\")[0]) \n",
    "薪水拆分[\"薪水\"]=薪水拆分列表\n",
    "薪水数量=薪水拆分.groupby(\"薪水\").agg({\"职称\":\"count\"})\n",
    "薪水数量=薪水数量.reset_index().sort_values(by=['职称'],ascending=False)\n",
    "\n",
    "def shuliang() -> Bar:\n",
    "  \n",
    "    bar = (\n",
    "        Bar()\n",
    "        .add_xaxis(list(薪水数量.薪水))\n",
    "        .add_yaxis(\"数量\",list(薪水数量.职称))\n",
    "        .set_global_opts(title_opts=opts.TitleOpts(title=\"网络直播各薪水段情况\"))\n",
    "    )\n",
    "\n",
    "\n",
    "    return bar\n",
    "\n",
    "shuliang().render_notebook()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 最多职位前10城市的招聘数量情况"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [
    {
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       "                \"\\u804c\\u4f4d\\u6570\\u91cf\"\n",
       "            ],\n",
       "            \"selected\": {\n",
       "                \"\\u804c\\u4f4d\\u6570\\u91cf\": true\n",
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       "    \"tooltip\": {\n",
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       "        \"textStyle\": {\n",
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       "    \"xAxis\": [\n",
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       "                    \"width\": 1,\n",
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       "                    \"curveness\": 0,\n",
       "                    \"type\": \"solid\"\n",
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       "                \"\\u4e0a\\u6d77\",\n",
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       "                \"\\u6df1\\u5733\",\n",
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       "                \"\\u6210\\u90fd\",\n",
       "                \"\\u9752\\u5c9b\",\n",
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       "    \"yAxis\": [\n",
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       "            \"scale\": false,\n",
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       "            \"nameGap\": 15,\n",
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       "        {\n",
       "            \"text\": \"\\u524d\\u5341\\u591a\\u62db\\u8058\\u7f51\\u7edc\\u76f4\\u64ad\\u804c\\u4f4d\\u7684\\u57ce\\u5e02\\u62db\\u8058\\u6570\\u91cf\\u60c5\\u51b5\",\n",
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       "                chart_e92e619a7e55483899aae7c9f80fed3a.setOption(option_e92e619a7e55483899aae7c9f80fed3a);\n",
       "        });\n",
       "    </script>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x25381df9f60>"
      ]
     },
     "execution_count": 110,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "最多职位城市=直播职位城市招聘数量.sort_values(by=['职称'],ascending=False)\n",
    "最多职位城市top10=最多职位城市.head(10)\n",
    "def chengshi() -> Bar:\n",
    "  \n",
    "    bar = (\n",
    "        Bar()\n",
    "        .add_xaxis(list(最多职位城市top10.公司所在城市))\n",
    "        .add_yaxis(\"职位数量\",list(最多职位城市top10.职称))\n",
    "        .set_global_opts(title_opts=opts.TitleOpts(title=\"前十多招聘网络直播职位的城市招聘数量情况\"))\n",
    "    )\n",
    "\n",
    "\n",
    "    return bar\n",
    "\n",
    "chengshi().render_notebook()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 职位[主题建模](https://baike.baidu.com/item/%E4%B8%BB%E9%A2%98%E6%A8%A1%E5%9E%8B/22777001?fr=aladdin)\n",
    "* 主题建模的目的：分析职位的关键词，分析出关键词的出现频率，从而帮助求职者找到网络直播行业的主要的职位的占比，以及相关能力的一些需求，让求职者更直观地了解网络直播行业的人才需求"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 清洗数据\n",
    "* 原因：由于数据中出现比较杂的数据，因此需要对数据进行清洗，去除无用信息，提交主题建模的准确度"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [],
   "source": [
    "#职称拆分=df[df[\"职称\"].str.contains(\"（\")]\n",
    "\n",
    "#职称拆分列表=list()\n",
    "#for x in 职称拆分[\"职称\"].to_list():\n",
    "#    职称拆分列表.append(x.split(\"（\")[0]) \n",
    "#职称拆分[\"职称\"]=职称拆分列表\n",
    "#职称拆分"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 利用join()对无关数据清洗"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
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      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 无关数据\n",
    "职位描述列表=df[\"职称\"].to_list()\n",
    "职位描述列表\n",
    "合并职称=\"\".join([a.strip() for a in 职位描述列表])\n",
    "合并职称\n",
    "处理=\"\".join(合并职称.split(\"\\t\"))\n",
    "information=处理.split(\"\\uf06c\") \n",
    "information"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 读入过滤词表格"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "利用到的[jieba库](https://blog.csdn.net/dongzixian/article/details/103240861)是什么？\n",
    "* 利用一个中文词库，确定汉字之间的关联概率\n",
    "* 汉字间概率大的组成词组，形成分词结果\n",
    "* 除了分词，用户还可以添加自定义的词组"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [],
   "source": [
    "import jieba\n",
    "fn = { \"input\" : { \"submissions\": \"submissions_profit_model_data_.xlsx\",\\\n",
    "                   \"user_dict_jieba\": \"user_dict_jieba_expanded.txt\",\\\n",
    "                   \"zh_stopwords\": \"stopwords_zh_both.txt\",\\\n",
    "                   \"word_freq_manual\": \"submissions_profit_model_word_freq_手动.xlsx\"\n",
    "                 } \n",
    "     }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [],
   "source": [
    "stop = [line.strip() for line in open(fn[\"input\"][\"zh_stopwords\"],\"r\",encoding=\"UTF-8-sig\").readlines()]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 建立函数并利用jieba分词模块过滤停止词并进行分词 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [],
   "source": [
    "fout = open('断词后结果.txt', 'w')\n",
    "def splitSentence(inputFile):\n",
    "    for eachLine in inputFile:\n",
    "        line = eachLine.strip()#.decode('utf-8', 'ignore')      #去除每行首尾可能出现的空格，并转为Unicode进行处理\n",
    "        line=line.strip('\\n')                                   #去掉多余空行\n",
    "        wordList = list(jieba.cut(line))\n",
    "        outStr = ''\n",
    "        for word in wordList:#\n",
    "            if len(word)>1:\n",
    "                if not word in stop:\n",
    "                        outStr += word\n",
    "                        outStr += ' '\n",
    "        fout.write(str(outStr.strip()))              #将分词好的结果写入到输出文件.encode('utf-8')\n",
    "        fout.write('\\n')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [],
   "source": [
    "splitSentence(information)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 读入分词后文档准备做数据主题建模"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "with open('断词后结果.txt' ,'r') as write:\n",
    "    text=write.read()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 根据后边建模的要求生成相应的列表"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "text1=[text.split(\" \")]# 嵌套列表\n",
    "text1\n",
    "word=text.split(\" \")#列表"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 主题建模\n",
    "* 使用模块:[gensim](https://radimrehurek.com/gensim/)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dictionary(405 unique tokens: ['120641', '15665', '1688', '32270', '5G']...)\n"
     ]
    }
   ],
   "source": [
    "from gensim.corpora import Dictionary\n",
    "import gensim\n",
    "\n",
    "from gensim import corpora, models\n",
    "from gensim.corpora.dictionary import Dictionary\n",
    "from gensim.models.ldamodel import LdaModel\n",
    "dictionary = Dictionary(text1)#嵌套词语列表\n",
    "print((dictionary))\n",
    "\n",
    "\n",
    "doc = [dictionary.doc2bow(word)]#词语列表"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "#num_topics是建模的主题数； num_words是建模的主题词显示个数\n",
    "ldamodel =LdaModel(corpus=doc, num_topics=5,id2word=dictionary)\n",
    "lda=ldamodel.print_topics(num_topics=5, num_words=30)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 主题建模可视化\n",
    "* 使用模块：[pyLDAvis](https://pyldavis.readthedocs.io/en/latest/readme.html)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<link rel=\"stylesheet\" type=\"text/css\" href=\"https://cdn.rawgit.com/bmabey/pyLDAvis/files/ldavis.v1.0.0.css\">\n",
       "\n",
       "\n",
       "<div id=\"ldavis_el1933625576830521203140079325\"></div>\n",
       "<script type=\"text/javascript\">\n",
       "\n",
       "var ldavis_el1933625576830521203140079325_data = {\"mdsDat\": {\"x\": [-0.034049154510833166, -0.02545127872903093, -0.00120450262128998, 0.029743787908246146, 0.03096114795290796], \"y\": [0.0016601565882358414, -0.002223605955223189, 0.00046638521524908314, 0.0020619553964321986, -0.0019648912446939637], \"topics\": [1, 2, 3, 4, 5], \"cluster\": [1, 1, 1, 1, 1], \"Freq\": [97.38021850585938, 2.581725597381592, 0.012765769846737385, 0.012646724469959736, 0.012643241323530674]}, \"tinfo\": {\"Term\": [\"\\u8fd0\\u8425\", \"\\u76f4\\u64ad\", \"\\u7ecf\\u7406\", \"\\u5de5\\u7a0b\\u5e08\", \"\\u7f51\\u7edc\", \"\\u9ad8\\u7ea7\", \"\\u5a92\\u4f53\", \"\\u4e3b\\u64ad\", \"\\u4e13\\u5458\", \"\\u9500\\u552e\", \"\\u5f00\\u53d1\", \"\\u8bb2\\u5e08\", \"\\u603b\\u76d1\", \"\\u6280\\u672f\", \"\\u8d44\\u6df1\", \"\\u57f9\\u8bad\", \"\\u6e38\\u620f\", \"\\u4ea7\\u54c1\", \"\\u6cd5\\u5f8b\\u987e\\u95ee\", \"\\u552e\\u524d\", \"\\u4e3b\\u7ba1\", \"\\u7535\\u5546\", \"\\u63a8\\u5e7f\", 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\"R\": 30, \"lambda.step\": 0.01, \"plot.opts\": {\"xlab\": \"PC1\", \"ylab\": \"PC2\"}, \"topic.order\": [5, 2, 4, 3, 1]};\n",
       "\n",
       "function LDAvis_load_lib(url, callback){\n",
       "  var s = document.createElement('script');\n",
       "  s.src = url;\n",
       "  s.async = true;\n",
       "  s.onreadystatechange = s.onload = callback;\n",
       "  s.onerror = function(){console.warn(\"failed to load library \" + url);};\n",
       "  document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "}\n",
       "\n",
       "if(typeof(LDAvis) !== \"undefined\"){\n",
       "   // already loaded: just create the visualization\n",
       "   !function(LDAvis){\n",
       "       new LDAvis(\"#\" + \"ldavis_el1933625576830521203140079325\", ldavis_el1933625576830521203140079325_data);\n",
       "   }(LDAvis);\n",
       "}else if(typeof define === \"function\" && define.amd){\n",
       "   // require.js is available: use it to load d3/LDAvis\n",
       "   require.config({paths: {d3: \"https://cdnjs.cloudflare.com/ajax/libs/d3/3.5.5/d3.min\"}});\n",
       "   require([\"d3\"], function(d3){\n",
       "      window.d3 = d3;\n",
       "      LDAvis_load_lib(\"https://cdn.rawgit.com/bmabey/pyLDAvis/files/ldavis.v1.0.0.js\", function(){\n",
       "        new LDAvis(\"#\" + \"ldavis_el1933625576830521203140079325\", ldavis_el1933625576830521203140079325_data);\n",
       "      });\n",
       "    });\n",
       "}else{\n",
       "    // require.js not available: dynamically load d3 & LDAvis\n",
       "    LDAvis_load_lib(\"https://cdnjs.cloudflare.com/ajax/libs/d3/3.5.5/d3.min.js\", function(){\n",
       "         LDAvis_load_lib(\"https://cdn.rawgit.com/bmabey/pyLDAvis/files/ldavis.v1.0.0.js\", function(){\n",
       "                 new LDAvis(\"#\" + \"ldavis_el1933625576830521203140079325\", ldavis_el1933625576830521203140079325_data);\n",
       "            })\n",
       "         });\n",
       "}\n",
       "</script>"
      ],
      "text/plain": [
       "PreparedData(topic_coordinates=              x         y  topics  cluster       Freq\n",
       "topic                                                \n",
       "4     -0.034049  0.001660       1        1  97.380219\n",
       "1     -0.025451 -0.002224       2        1   2.581726\n",
       "3     -0.001205  0.000466       3        1   0.012766\n",
       "2      0.029744  0.002062       4        1   0.012647\n",
       "0      0.030961 -0.001965       5        1   0.012643, topic_info=    Term        Freq       Total Category  logprob  loglift\n",
       "383   运营  129.000000  129.000000  Default  30.0000  30.0000\n",
       "308   直播   94.000000   94.000000  Default  29.0000  29.0000\n",
       "326   经理   69.000000   69.000000  Default  28.0000  28.0000\n",
       "205  工程师   49.000000   49.000000  Default  27.0000  27.0000\n",
       "337   网络   41.000000   41.000000  Default  26.0000  26.0000\n",
       "..   ...         ...         ...      ...      ...      ...\n",
       "193   客户    0.000768    7.886085   Topic5  -5.5676  -0.2612\n",
       "373  负责人    0.000792    8.775908   Topic5  -5.5367  -0.3372\n",
       "229   执行    0.000829   10.228213   Topic5  -5.4906  -0.4442\n",
       "116  分析师    0.000828   10.271503   Topic5  -5.4917  -0.4496\n",
       "158   售前    0.000860   15.129345   Topic5  -5.4547  -0.7998\n",
       "\n",
       "[353 rows x 6 columns], token_table=      Topic      Freq     Term\n",
       "term                          \n",
       "1         1  0.911057    15665\n",
       "6         1  0.813735       6K\n",
       "9         1  0.951387  Android\n",
       "10        1  0.811529      B2B\n",
       "11        1  0.870227      C++\n",
       "...     ...       ...      ...\n",
       "395       1  0.888368       项目\n",
       "398       1  1.018570       顾问\n",
       "400       1  0.935495       风险\n",
       "403       1  0.962272       高级\n",
       "403       2  0.026730       高级\n",
       "\n",
       "[139 rows x 3 columns], R=30, lambda_step=0.01, plot_opts={'xlab': 'PC1', 'ylab': 'PC2'}, topic_order=[5, 2, 4, 3, 1])"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pyLDAvis\n",
    "import pyLDAvis.gensim  # don't skip this\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import logging\n",
    "logging.basicConfig(format='%(asctime)s : %(levelname)s : %(message)s', level=logging.ERROR)\n",
    "\n",
    "import warnings\n",
    "warnings.filterwarnings(\"ignore\",category=DeprecationWarning)\n",
    "pyLDAvis.enable_notebook()\n",
    "vis = pyLDAvis.gensim.prepare(ldamodel, doc, dictionary)\n",
    "\n",
    "vis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "#生成html文件\n",
    "pyLDAvis.save_html(vis,\"国内网络直播行业职称主题建模.html\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 建立词频字典"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "counts = {}\n",
    "for a in word:  \n",
    "    counts[a] = counts.get(a,0) + 1\n",
    "items = list(counts.items())  \n",
    "items.sort(key=lambda x:x[1], reverse=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
       "<script>\n",
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       "            'echarts':'https://assets.pyecharts.org/assets/echarts.min', 'echarts-wordcloud':'https://assets.pyecharts.org/assets/echarts-wordcloud.min'\n",
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       "    });\n",
       "</script>\n",
       "\n",
       "        <div id=\"a5761c9611cd4c6289386c7ef3fa6709\" style=\"width:900px; height:500px;\"></div>\n",
       "\n",
       "<script>\n",
       "        require(['echarts', 'echarts-wordcloud'], function(echarts) {\n",
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       "    \"animationDuration\": 1000,\n",
       "    \"animationEasing\": \"cubicOut\",\n",
       "    \"animationDelay\": 0,\n",
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       "    \"animationEasingUpdate\": \"cubicOut\",\n",
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       "    \"color\": [\n",
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       "                    \"textStyle\": {\n",
       "                        \"normal\": {\n",
       "                            \"color\": \"rgb(158,41,74)\"\n",
       "                        }\n",
       "                    }\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u6587\\u5316\\u8bfe\",\n",
       "                    \"value\": 1,\n",
       "                    \"textStyle\": {\n",
       "                        \"normal\": {\n",
       "                            \"color\": \"rgb(71,130,34)\"\n",
       "                        }\n",
       "                    }\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u5ba1\\u8ba1\",\n",
       "                    \"value\": 1,\n",
       "                    \"textStyle\": {\n",
       "                        \"normal\": {\n",
       "                            \"color\": \"rgb(146,15,31)\"\n",
       "                        }\n",
       "                    }\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u5fae\\u7279\\u559c\",\n",
       "                    \"value\": 1,\n",
       "                    \"textStyle\": {\n",
       "                        \"normal\": {\n",
       "                            \"color\": \"rgb(98,19,43)\"\n",
       "                        }\n",
       "                    }\n",
       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u5f71\\u97f3\",\n",
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       "                    \"textStyle\": {\n",
       "                        \"normal\": {\n",
       "                            \"color\": \"rgb(99,86,60)\"\n",
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       "                },\n",
       "                {\n",
       "                    \"name\": \"\\u526f\\u603b\\u7ecf\\u7406\",\n",
       "                    \"value\": 1,\n",
       "                    \"textStyle\": {\n",
       "                        \"normal\": {\n",
       "                            \"color\": \"rgb(119,33,65)\"\n",
       "                        }\n",
       "                    }\n",
       "                }\n",
       "            ],\n",
       "            \"drawOutOfBound\": false,\n",
       "            \"textStyle\": {\n",
       "                \"emphasis\": {}\n",
       "            }\n",
       "        }\n",
       "    ],\n",
       "    \"legend\": [\n",
       "        {\n",
       "            \"data\": [],\n",
       "            \"selected\": {},\n",
       "            \"show\": true,\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10,\n",
       "            \"itemWidth\": 25,\n",
       "            \"itemHeight\": 14\n",
       "        }\n",
       "    ],\n",
       "    \"tooltip\": {\n",
       "        \"show\": true,\n",
       "        \"trigger\": \"item\",\n",
       "        \"triggerOn\": \"mousemove|click\",\n",
       "        \"axisPointer\": {\n",
       "            \"type\": \"line\"\n",
       "        },\n",
       "        \"textStyle\": {\n",
       "            \"fontSize\": 14\n",
       "        },\n",
       "        \"borderWidth\": 0\n",
       "    },\n",
       "    \"title\": [\n",
       "        {\n",
       "            \"text\": \"\\u56fd\\u5185\\u7f51\\u7edc\\u76f4\\u64ad\\u884c\\u4e1a\\u804c\\u79f0\\u5173\\u952e\\u8bcd\",\n",
       "            \"padding\": 5,\n",
       "            \"itemGap\": 10\n",
       "        }\n",
       "    ]\n",
       "};\n",
       "                chart_a5761c9611cd4c6289386c7ef3fa6709.setOption(option_a5761c9611cd4c6289386c7ef3fa6709);\n",
       "        });\n",
       "    </script>\n"
      ],
      "text/plain": [
       "<pyecharts.render.display.HTML at 0x25381d2ec88>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import json\n",
    "\n",
    "from pyecharts import options as opts\n",
    "from pyecharts.charts import WordCloud\n",
    "\n",
    "# with open(\"wordcloud_image_base64.json\", \"r\", encoding=\"utf-8\") as f:\n",
    "#     j = json.load(f)\n",
    "counts = {}\n",
    "for a in word:  \n",
    "    counts[a] = counts.get(a,0) + 1\n",
    "items = list(counts.items())  \n",
    "items.sort(key=lambda x:x[1], reverse=True)\n",
    "items\n",
    "\n",
    "c = (\n",
    "    WordCloud()\n",
    "    .add(\"\",items, word_size_range=[12, 55])#, mask_image=j[\"base64\"]\n",
    "    .set_global_opts(title_opts=opts.TitleOpts(title=\"国内网络直播行业职称关键词\"))\n",
    "    #.render(\"网络直播职称词云图.html\")\n",
    ")\n",
    "c.render_notebook()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  国内网络直播行业职称关键词[词云图](https://baike.baidu.com/item/%E8%AF%8D%E4%BA%91/6952822?fr=aladdin)\n",
    "\n",
    "    从上面主题建模及词云图得出的数据结果来看，国内的网络直播行业职称的不仅仅是专注于网络直播的主播行业，还有工程师、运营、经理、法律等领域，对人才也会有语言、编程能力和其他能力的要求，网络直播行业对人才的需求要求还是比较多元的，更多的求职者可以考虑网络直播行业。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 总结\n",
    "总结以上图表及分析可知，   \n",
    "国内网络直播行业的主要需求是经济较发达是城市，主要集中于东部沿海与长江流域地区；  \n",
    "对就业者的学历要求主要是本科以上、学历不限和大专以上，这三个学历要求占多数，对学历的要求不算很高；  \n",
    "对求职者的经验要求主要是经验不限、1-3年和3-5年，可看出行业对经验要求不高；  \n",
    "且通过职称关键词词云图分析得知，网络直播行业所需要的人才较多元。  \n",
    "从薪水段排名柱形图来看，网络直播职位多集中6-8k,10-15k,15-30k,5-8k之间，薪水情况较好。  \n",
    "前十多招聘网络直播职位的城市招聘数量情况柱形图来看，求职者可前往北京、广州、上海、杭州、深圳等招聘职位较多的城市求职。  \n",
    "综上，网络直播职位的行业前景较好，求职者只要通过要求数据的分析找出目标职位的要求与自己的优势匹配，早日找到相关工作。\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 最小可行性产品介绍\n",
    "* 本网页为最小可行性产品，有图分析也有文字说明，让求职者得到更多信息。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 心得及总结\n",
    "* 本次课程与实践我学习到很多关于数据分析的知识，但是除了必要的数据分析能力，我们还学习了数据分析思维，我们要结合人文来进行科学的数据分析，一切从人出发，并思考加值部分。\n",
    "* 本次课程和学习，同行给予很大的帮助，并借鉴参考他们的项目，更明确的学习到清晰的数据分析思路。\n",
    "* 非常感谢同学的辛勤付出与帮助\n",
    "* 也感谢老师提供的[代码](https://gitee.com/InternetNewMedia/Spring20_Pandas)帮助与[教学](http://e.nfu.edu.cn/course/view.php?id=64#section-18)"
   ]
  },
  {
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   "metadata": {},
   "source": []
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